Prospects of Retrieval-Augmented Generation (RAG) for Academic Library Search and Retrieval

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Information Technology and Libraries (Online) vol. 44, no. 2 (Jun 2025), p. 1-16
1. Verfasser:	Bevara, Ravi Varma Kumar
Weitere Verfasser:	Lund, Brady D, Mannuru, Nishith Reddy, Karedla, Sai Pranathi, Mohammed, Yara, Kolapudi, Sai Tulasi, Mannuru, Aashrith
Veröffentlicht:	American Library Association
Schlagworte:	Libraries Knowledge bases (artificial intelligence) Computer architecture Credibility Library collections User experience Middleware Large language models Academic libraries Searching Retrieval Real time Ethics Query processing Information retrieval Natural language Transparency Copyright Databases Conversation Research Infrastructure Human-computer interaction Cost analysis Regulation Semantic processing Compliance Privacy Data processing Interfaces Integrated care Indexing Augmentation Pipelines Language modeling Data integrity Library Materials Semantics Copyrights Research Needs Architecture Video Technology Influence of Technology Researchers Library Services Library Networks Information Needs Metadata Feedback (Response) Accuracy Opportunities Interdisciplinary Approach Database Management Systems Academic Standards Educational Needs
Online-Zugang:	Citation/Abstract Full Text Full Text - PDF
Tags:	Tag hinzufügen Keine Tags, Fügen Sie das erste Tag hinzu!

Beschreibung
Abstract:	This paper examines the integration of retrieval-augmented generation (RAG) systems within academic library environments, focusing on their potential to transform traditional search and retrieval mechanisms. RAG combines the natural language understanding capabilities of large language models with structured retrieval from verified knowledge bases, offering a novel approach to academic information discovery. The study analyzes the technical requirements for implementing RAG in library systems, including embedding pipelines, vector databases, and middleware architecture for integration with existing library infrastructure. We explore how RAG systems can enhance search precision through semantic indexing, real-time query processing, and contextual understanding while maintaining compliance with data privacy and copyright regulations. The research highlights RAG's ability to improve user experience through personalized research assistance, conversational interfaces, and multimodal content integration. Critical considerations including ethical implications, copyright compliance, and system transparency are addressed. Our findings indicate that while RAG presents significant opportunities for advancing academic library services, successful implementation requires careful attention to technical architecture, data protection, and user trust. The study concludes that RAG integration holds promise for revolutionizing academic library services while emphasizing the need for continued research in areas of scalability, ethical compliance, and cost-effective implementation.
ISSN:	2163-5226
DOI:	10.5860/ital.v44i2.17361
Quelle:	ABI/INFORM Global